The 'truth serum' for AI: OpenAI’s new method for training models to confess their mistakes

The research offers a practical way to monitor for scheming and hallucinations, a critical step for high-stakes enterprise ...

Google’s ‘Nested Learning’ paradigm could solve AI's memory and continual learning problem

Inspired by how the human brain consolidates memory, the 'Nested Learning' framework allows different parts of a model to ...
Communications of the ACM

Learning How Learning Works

“Based on their training data, they just model the probability that a given token, or word, will follow a set of tokens that ...

OpenAI prompts AI models to ‘confess’ when they cheat

The idea is to make LLMs turn themselves in when they don’t follow instructions, potentially reducing errors in enterprise ...
International Monetary Fund

GDP Nowcasting Performance of Traditional Econometric Models vs Machine-Learning Algorithms: Simulation and Case Studies

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting?
Geeky Gadgets

Machine Learning vs Deep Learning vs Foundation Models

If you are interested in learning more about artificial intelligence and specifically how different areas of AI relate to each other then this quick guide providing an overview of Machine Learning vs ...

Flood disaster prediction using multi-scale deep learning and neuro-fuzzy inference

A new algorithmic framework that can predict flooding could help save lives and reduce the devastation as climate change drives more intense and unpredictable rainfall.

Machine learning model sharpens snowfall forecasts for the Mountain West

The varied topography of the Western United States—a patchwork of valleys and mountains, basins and plateaus—results in minutely localized weather. Accordingly, snowfall forecasts for the mountain ...